JMIR Medical Education

Although digital health is essential for improving health care, its adoption remains slow due to the lack of literacy in this area. Therefore, it is crucial for health professionals to acquire digital skills and for a digital competence assessment and accreditation model to be implemented to make advances in this field.

ncremental advancements in Artificial Intelligence (AI) technology have facilitated its integration into various disciplines. In particular, the infusion of AI into medical education has emerged as a significant trend with noteworthy research findings. Consequently, a comprehensive review and analysis of the current research landscape of AI in medical education is warranted.

The 2024 Nephrology fellowship match data shows the declining interest in Nephrology in the United States, with an 11% drop in candidates and a mere 66% of positions filled.

Current challenges in patient care have increased research on technology use in nursing and health care. Digital assistive technologies (DATs) are one option that can be incorporated into care processes. However, how the application of DATs should be introduced to nurses and care professionals must be clarified. No structured and effective education concepts for the patient-oriented integration of DATs in the nursing sector are currently available.

This research explores the capabilities of ChatGPT-4 in passing the American Board of Family Medicine (ABFM) Certification Examination. Addressing a gap in existing literature, where earlier Artificial Intelligence (AI) models showed limitations in medical board exams, this study evaluates the enhanced features and potential of ChatGPT-4, especially in document analysis and information synthesis.

The integration of gender and sexuality awareness in health care is increasingly recognized as vital for patient outcomes. Despite this, there is a notable lack of comprehensive data on the current state of physicians’ training and perceptions in these areas, leading to a gap in targeted educational interventions and optimal health care delivery.

In the field of research, psychological safety has been widely recognized as a contributing factor to improving the quality of care and patient safety. However, its consideration in the curricula and traineeship pathways of residents and health care students is scarce.

The creation of large language models (LLMs) such as ChatGPT is an important step in the development of artificial intelligence(AI), which shows great potential in medical education due to its powerful language understanding and generative capabilities. The purpose of this study was to quantitatively evaluate and comprehensively analyze ChatGPT's performance in handling questions for the National Nursing Licensure Examination in China and the United States, including the National Council Licensure Examination for Registered Nurses (NCLEX-RN) and the National Nursing Licensure Examination (NNLE).

Limited digital literacy is a barrier for vulnerable patients accessing health care.

The Objective Structured Clinical Examination (OSCE) is a pivotal tool for assessing health care professionals and plays an integral role in medical education.

An integration of digital medicine into medical education can help future physicians shape the digital transformation of medicine.

Instructional and clinical technologies have been transforming dental education. With the emergence of artificial intelligence (AI), the opportunities of utilizing AI in education has increased. With the recent advancement of generative AI, Large Language Models (LLMs) and foundation models (FM) gained attention with their capabilities in natural language understanding and generation as well as combining multiple types of data, such as text, images, and audio. A common example has been ChatGPT, which is based on a powerful LLM, generative pretrained transformer (GPT) model. This article discusses the potential benefits and challenges of incorporating LLMs in dental education, focusing on periodontal charting with a use case to outline capabilities of LLMs. LLMs can provide personalized feedback, generate case scenarios, and create educational content to contribute to the quality of dental education. However, challenges, limitations and risks exist, including bias and inaccuracy in the content created, privacy and security concerns, and the risk of overreliance. With the guidance and oversight, and by effectively and ethically integrating LLMs, dental education can incorporate engaging and personalized learning experiences for students towards readiness for real-life clinical practice.